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Turkey’s Green Imagination: the Spatiality of the Low-Carbon Energy Transition Within the Eu Green Deal
No full textThis article asks the extent to which the EU Green Deal influences the EU periphery today and builds on the spatial conditions of multiple, co-existing decarbonization pathways within the EU Green Deal while problematizing the ‘green imagination’ of Turkey as an immediate neighbour and a candidate country for membership in the EU. As such, it uncovers that the current low-carbon transition process in Turkey is prone to be shaped by the highly politicized energy market in an authoritarian neoliberal structure on the one hand, and Turkey’s priorities in energy issues and hard security on the other. The findings further reveal that Turkey’s efforts to use more domestic energy resources to meet its consumption needs might also interfere with its efforts and obligations to decarbonize its energy sector. The scrutiny into the low-carbon energy transition in Turkey accordingl contributes further insight into the consequences of the spatiality of such transitions in an authoritarian neoliberal context, and what other alternative policies can be imagined and put in practice. Thus, more empirical research is warranted to reveal the spatiality of the low-carbon energy transition across various geographical settings. At the same time, the article argues that both the EU and its partners such as Turkey should be weary of creating green utopias when redesigning their green-energy space since utopias tout court may not always stimulate large-scale change in a revolutionary way in terms of sustainability, feasibility, good practice, and inclusiveness in decision-making processes
Görünür Işikla Haberleşmede Karartma Etkisi Altinda Fiziksel Katman Güvenliǧi
No full textIstanbul Technical University (ITU); TUBITAK BILGEM; TurkcellVisible Light Communication (VLC) is a promising option for 6G wireless systems to increase performance and provide a high-speed data rate compared to radio frequency (RF). Dimming control is one of the most important aspects to be considered in VLC. It is very critical for the future of VLC to adjust the brightness of the light source to be used in communication and to ensure that the light source, with a changing brightness, maintains the desired communication performance due to the situation and environment. This work proposes a novel pilot-aided estimation method for channel and dimming coefficients in spatial modulation (SM)-VLC systems. As a result, in the VLC system running with the PLS algorithm, while the information transmitted to the legal user is received with an excellent BER performance, it is observed that the BER performance of the eavesdropper is around 0.5, which is the worst possible situation for the illegal user. © 2023 IEEE
On-Demand Continuous-Variable Quantum Entanglement Source for Integrated Circuits
Get PDFIntegration of devices generating non-classical states (such as entanglement) into photonic circuits is one of the major goals in achieving integrated quantum circuits (IQCs). This is demonstrated successfully in recent decades. Controlling the non-classicality generation in these micron scale devices is also crucial for the robust operation of the IQCs. Here, we propose a micron-scale quantum entanglement device whose nonlinearity (so the generated non classicality) can be tuned by several orders of magnitude via an applied voltage without altering the linear response. Quantum emitters (QEs), whose level-spacing can be tuned by voltage, are embedded into the hotspot of a metal nanostructure (MNS). QE-MNS coupling introduces a Fano resonance in the nonlinear response. Nonlinearity, already enhanced extremely due to localization, can be controlled by the QEs' level-spacing. Nonlinearity can either be suppressed or be further enhanced by several orders. Fano resonance takes place in a relatively narrow frequency window so that similar to meV voltage-tunability for QEs becomes sufficient for a continuous turning on/off of the non-classicality. This provides as much as 5 orders of magnitude modulation depths.[TUBITAK-1001]; [114F170]; [117F118]Acknowledgements PD and MET acknowledge support from TUBITAK-1001 Grant No: 114F170. MG and MET acknowledge support from TUBITAK-1001 Grant No: 117F118
An Energy-Aware Scheme for Solving the Routing Problem in the Internet of Things Based on Jaya and Flower Pollination Algorithms
No full textClustering and routing protocols for Internet of Things (IoT) need to consider energy usage and how to reduce it. Unbalanced power usage is a common concern with current solutions to cluster-based routing problems in the IoT ecosystem. This research developed a swarm intelligence-based clustering technique to achieve a more uniform dispersion of cluster heads. The data packets across cluster heads and the sink are routed via a Jaya algorithm. Based on average remaining energy, number of active nodes, number of nodes that have failed or have been removed from the network, and overall network throughput, this combined clustering and routing method's quality has been assessed. The integrative clustering and routing protocol based on the flower pollination algorithm and Jaya algorithm described here exhibit considerable improvements over the current state-of-the-art. The network throughput and the number of the alive node are essential statistics for evaluating IoT in which battery-powered devices periodically acquire surroundings data and transmit gathered samples to a base station. The proposed strategy improved network throughput and the number of dead nodes by at least 14% and 18%, respectively. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature
Exploring Non-Linear Relationships Between Perceived Interactivity or Interface Design and Acceptance of Collaborative Web-Based Learning
Get PDFThe novelty of this study is in developing a conceptual model for predicting the non-linear relationships between human-computer interaction factors and ease of use and usefulness of collaborative web-based learning or e-learning. Ten models (logarithmic, inverse, quadratic, cubic, compound, power, s-curve, growth, exponential, and logistic) were examined as functions of effects compared to linear relationships to see which was the most appropriate, based on R-2, adjusted R-2 and SEE values. To answer the addressed questions, the researcher surveyed 103 students from Kadir Has University about the perceived interface and interactivity of e-learning. The results show that most of the hypotheses formulated for this purpose have been proven. Our analysis shows that cubic models (the relationship between ease of use and usefulness, visual design, course environment, learner-interface interactivity, and course evaluation system and ease of use), quadratic models (the relationship between visual design, and system quality and usefulness, course structure and content, course environment, and system quality and ease of use), logarithmic model (the relationship between course evaluation system and usefulness), and s-curve models (learner-interface interactivity, navigation, and course structure and content and usefulness) performed better in the description for the correlations
Scholarly Publishing in Tourism and Feelings of Envy: Impacts on Emotional Exhaustion, Job Satisfaction, and Life Satisfaction
No full textKozak, Metin/0000-0002-9866-7529Research is the core of academic life. However, unlike its traditional structure, academia has become increasingly competitive due to the increasing expectation of publications through international rankings. Scholars put more effort into publishing, teaching, and other commitments. Over the years, the number of co-authored articles has also increased. Therefore, this study aims to empirically investigate the effects of journal selection on scholars' burnout and envy feelings and analyze its direct impacts on job and life satisfaction. Our results are based on the assessment of 291 questionnaire surveys collected among scholars studying tourism and affiliated with different countries. Results confirm the continuous publish-or-perish trend, and it discloses the unspoken agenda of academia by proving the inciting role of well-known journals over scholars studying tourism
Cruel Optimism of Waiting: Precarity Experiences of Young Adults in Turkey
No full textKUCUK, BERMAL/0000-0002-5481-7687; Cobek, Gozde/0000-0003-4732-2077; Cemalcilar, Zeynep/0000-0002-0886-7982This paper examines young adults' everyday experiences of precarity. Defining precarity as a socioeconomic and affective condition, it offers waiting as an analytical tool to explore the intersection of precarity and the family as a locus of social security and dependency. Based on the in-depth interviews with young adults (N = 52), it investigates the affective and temporal dimensions of precarity that play out in the waiting practices of young adults in Turkey. Focusing on these practices, we show how conditions of precarity foster an entrepreneurial mindset and never-ending self-enterprise while establishing forms of cruel attachments and dependencies. Following Berlant's notion of cruel optimism, we demonstrate how young adults become paradoxically dependent on their familial bonds and temporary job market to become independent individuals. We conclude that the family as an agent of individualization and normalization of precarity (re-)emerges as the backbone of neoliberal restructuring. However, such familial bonds within the context of fragmented biographies reinforce cruel attachments in which sustaining the aspirations for independence makes precarious young adults more dependent on their families.Scientific and Technological Research Council of TurkeyNo Statement Availabl
Zamanla Değişen Ofdm Sistemlerde Yapay Sinir Ağı Tabanlı Kanal Kestirimi
No full textLTE gibi sistemler sayesinde, maksimum 100 Mbit/s'ye kadar veri hızlarına ulaşmak mümkün olmaktadır. Ancak, bu hızlara kullanıcı tarafındaki hareketliliğin olmadığı veya düşük olduğu senaryolarda erişilebilir. Kullanıcının hareket hızı arttıkça, kanal kestirimi yönteminin düşük kompleksiteye sahip olması gerekliliği de artmaktadır, çünkü kanalın zamana bağımlı özelliği kötüleşmektedir. Derin öğrenme, birçok sektörde geleneksel yöntemlerin yavaş yavaş yerini almaya başlayarak, çeşitli alanlarda sıkça kullanılır hale gelmektedir. Derin öğrenmenin hesaplama karmaşıklığını azaltmak ve sistem performansını artırmak hakkındaki kabiliyeti kanıtlanmıştır. Bu tez, derin sinir ağları (DNN) kullanarak zamana bağlı ortogonal frekans bölmeli çoklu erişim (OFDM) kanalları için bir kanal kestirimi yöntemi önermektedir. Kanal kestiriminin hesaplama karmaşıklığını azaltmak için zamana bağlı hızla değişen OFDM kanalını temsil etmek için Legendre polinom katsayıları kullanılmaktadır. Lineer minimum ortalama karesel hata (LMMSE) kullanılarak kanalı temsil eden polinom katsayılarının başlangıç değerleri kestirilmiş ve kestirim doğruluğu DNN ile arttırılmıştır. Sonuçlar, mekansal alternatif genelleştirilmiş beklenti maksimizasyonu - maksimum a posteriori olasılık (SAGE-MAP) ve LMMSE kanal kestirim yöntemi ile karşılaştırılmaktadır. Düşük sinyal-gürültü oranlarında DNN temelli kestirim daha küçük ortalama karesel hata (MSE) ve sembol hata oranları (SER) elde edildiği gösterilmiştir.Systems like LTE makes it possible to reach data rates up to a maximum of 100Mbit/s. However, these bit rates are accessible when there is nomadic mobility at the user end. As the user's movement speed increases, the necessity of a low-complexity channel estimation method is also increasing because the time-invariant feature of the channel deteriorates. Deep learning is increasingly embedded in various fields and slowly replacing conventional methods across many sectors. It has already proven its capability to decrease computational complexity and increase the system's performance. This thesis proposes a channel estimation method for time-varying orthogonal frequency division multiplexing (OFDM) channels using deep neural networks (DNN). We utilize a Legendre polynomial approach to represent the rapidly changing time-varying OFDM channel to reduce the computational complexity of the estimation. Using linear minimum mean-square error (LMMSE), initial values of the polynomial coefficients that represent the channel are estimated, and the estimation accuracy has been improved with DNN. The results are compared with an iterative estimation algorithm that is space alternating generalized expectation maximization—maximum a posteriori probability (SAGE-MAP) and LMMSE estimation. It is shown that smaller mean square error (MSE) and symbol error rates (SER) were obtained with DNN-based estimation at lower signal-to-noise ratios
Improving Diabetic Retinopathy Detection Using Patchwise Cnn With Bigru Model
No full textThis study addresses Diabetic Retinopathy (DR), a diabetes complication that can lead to vision loss if not promptly diagnosed and treated. Recent advances in deep learning have shown promising results in detecting DR from retinal images. The study introduces a novel patch-based CNN-biGRU model for DR detection. The proposed model extracts patches from retinal images employing a sliding window strategy and then uses a Convolutional Neural Network (CNN) architecture to extract features from each patch. The features extracted from each patch are then concatenated, and a 4-layer bidirectional Gated Recurrent Unit (biGRU) is applied to predict the whole image. We assessed the proposed model on a publicly available dataset named APTOS 2019 Blindness Detection and achieved an accuracy of 73.5%, outperforming existing state-of-the-art approaches. The given patch-based CNN model can improve the accuracy of DR detection and aims to assist ophthalmologists in making more accurate diagnoses. © 2023 IEEE
A Novel Model Based on the Fuzzy Grey Relational Analysis (f-Gra) Approach for Selecting the Appropriate High-Speed Train Set
No full textThe high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic